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KDD
2008
ACM
239views Data Mining» more  KDD 2008»
16 years 6 months ago
Mining adaptively frequent closed unlabeled rooted trees in data streams
Closed patterns are powerful representatives of frequent patterns, since they eliminate redundant information. We propose a new approach for mining closed unlabeled rooted trees a...
Albert Bifet, Ricard Gavaldà
KDD
2008
ACM
161views Data Mining» more  KDD 2008»
16 years 6 months ago
Spectral domain-transfer learning
Traditional spectral classification has been proved to be effective in dealing with both labeled and unlabeled data when these data are from the same domain. In many real world ap...
Xiao Ling, Wenyuan Dai, Gui-Rong Xue, Qiang Yang, ...
KDD
2007
ACM
159views Data Mining» more  KDD 2007»
16 years 6 months ago
Constraint-driven clustering
Clustering methods can be either data-driven or need-driven. Data-driven methods intend to discover the true structure of the underlying data while need-driven methods aims at org...
Rong Ge, Martin Ester, Wen Jin, Ian Davidson
KDD
2007
ACM
165views Data Mining» more  KDD 2007»
16 years 6 months ago
Finding low-entropy sets and trees from binary data
The discovery of subsets with special properties from binary data has been one of the key themes in pattern discovery. Pattern classes such as frequent itemsets stress the co-occu...
Eino Hinkkanen, Hannes Heikinheimo, Heikki Mannila...
KDD
2007
ACM
182views Data Mining» more  KDD 2007»
16 years 6 months ago
Cleaning disguised missing data: a heuristic approach
In some applications such as filling in a customer information form on the web, some missing values may not be explicitly represented as such, but instead appear as potentially va...
Ming Hua, Jian Pei